このコースについて
554,260 最近の表示

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.

約7時間で修了

推奨:4 weeks, 4-5 hours/week...

英語

字幕:英語

学習内容

  • Check

    Learn best practices for using TensorFlow, a popular open-source machine learning framework

  • Check

    Build a basic neural network in TensorFlow

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    Train a neural network for a computer vision application

  • Check

    Understand how to use convolutions to improve your neural network

習得するスキル

Computer VisionTensorflowMachine Learning

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.

約7時間で修了

推奨:4 weeks, 4-5 hours/week...

英語

字幕:英語

シラバス - 本コースの学習内容

1
3時間で修了

A New Programming Paradigm

Welcome to this course on going from Basics to Mastery of TensorFlow. We're excited you're here! In week 1 you'll get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study...

...
4件のビデオ (合計16分), 5 readings, 3 quizzes
4件のビデオ
A primer in machine learning3 分
The ‘Hello World’ of neural networks5 分
Working through ‘Hello World’ in TensorFlow and Python3 分
5件の学習用教材
Learner Support10 分
From rules to data10 分
Try it for yourself10 分
Introduction to Google Colaboratory10 分
Week 1 Resources10 分
1の練習問題
Week 1 Quiz
2
4時間で修了

Introduction to Computer Vision

Welcome to week 2 of the course! In week 1 you learned all about how Machine Learning and Deep Learning is a new programming paradigm. This week you’re going to take that to the next level by beginning to solve problems of computer vision with just a few lines of code! Check out this conversation between Laurence and Andrew where they discuss it and introduce you to Computer Vision!

...
7件のビデオ (合計15分), 6 readings, 3 quizzes
7件のビデオ
An Introduction to computer vision2 分
Writing code to load training data2 分
Coding a Computer Vision Neural Network2 分
Walk through a Notebook for computer vision3 分
Using Callbacks to control training1 分
Walk through a notebook with Callbacks1 分
6件の学習用教材
Exploring how to use data10 分
The structure of Fashion MNIST data10 分
See how it's done10 分
Get hands-on with computer vision1 時間
See how to implement Callbacks10 分
Week 2 Resources10 分
1の練習問題
Week 2 Quiz
3
5時間で修了

Enhancing Vision with Convolutional Neural Networks

Welcome to week 3! In week 2 you saw a basic Neural Network for Computer Vision. It did the job nicely, but it was a little naive in its approach. This week we’ll see how to make it better, as discussed by Laurence and Andrew here.

...
6件のビデオ (合計19分), 6 readings, 3 quizzes
6件のビデオ
What are convolutions and pooling?2 分
Implementing convolutional layers1 分
Implementing pooling layers4 分
Improving the Fashion classifier with convolutions4 分
Walking through convolutions3 分
6件の学習用教材
Coding convolutions and pooling layers10 分
Learn more about convolutions10 分
Getting hands-on, your first ConvNet10 分
Try it for yourself1 時間
Experiment with filters and pools1 時間
Week 3 Resources10 分
1の練習問題
Week 3 Quiz
4
6時間で修了

Using Real-world Images

Last week you saw how to improve the results from your deep neural network using convolutions. It was a good start, but the data you used was very basic. What happens when your images are larger, or if the features aren’t always in the same place? Andrew and Laurence discuss this to prepare you for what you’ll learn this week: handling complex images!

...
9件のビデオ (合計27分), 10 readings, 3 quizzes
9件のビデオ
Understanding ImageGenerator4 分
Defining a ConvNet to use complex images2 分
Training the ConvNet with fit_generator2 分
Walking through developing a ConvNet2 分
Walking through training the ConvNet with fit_generator3 分
Adding automatic validation to test accuracy4 分
Exploring the impact of compressing images3 分
Outro: A conversation with Andrew1 分
10件の学習用教材
Explore an impactful, real-world solution10 分
Designing the neural network10 分
Train the ConvNet with ImageGenerator10 分
Exploring the solution10 分
Training the neural network10 分
Experiment with the horse or human classifier1 時間
Get hands-on and use validation30 分
Get Hands-on with compacted images30 分
Week 4 Resources10 分
Outro10 分
1の練習問題
Week 4 Quiz
4.6
291件のレビューChevron Right

44%

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コースが具体的なキャリアアップにつながった

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning からの人気レビュー

by ASMar 9th 2019

Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?

by AWJun 7th 2019

An awesome practical course that helps me to start creating my first neural networks using keras in such great methods, the instructor is very good at delivering the knowledge he has\n\n.

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Laurence Moroney

AI Advocate
Google Brain

deeplearning.aiについて

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

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